This is a marketing analytics scenario.
Jeremy traded US stocks for a few years, but is now thinking about broadening his trading to oil, gold and international stocks.
On wsj.com, he reads about the virtues of diversification through the use of international stocks. Next to the article, a BankCorp banner shows a picture of a cool, confident investor who trades stocks in Deutsche Bank and China Telecom from his cell phone. Jeremy does not click on the banner, but a cookie is placed on Jeremy's computer and he makes a subconscious association between BankCorp and trading.
A few days later, Jeremy hears that Bet24, the large bookmaker traded on the Austrian stock exchange, is undervalued and decides to act on the information. Now he needs a financial services provider right away. Jeremy does a Google search using the keywords “stock trading” and “austrian stocks”. Next to the organic search hits, the Google Adwords ads shows a BankCorp ad as the third advertisement, specifically mentioning the possibility of trading Austrian stocks. Jeremy clicks on BankCorp's ad because he has seen the name before.
On BankCorp's landing page, their trading platform's international stock trading capability is emphasized at the center of the page. The website registers what AdWords ad led to the website, along with Jeremy's search keywords. Jeremy is from New York City, a fact that is revealed and registered through his IP address. Finally, it is noted that Jeremy was once exposed to a wsj.com international stock ad.
Jeremy is curious about the price of real-time price feeds, the range of available stock exchanges and types of tradable commodities, but it also occurs to him to search for what kind of guarantee he has that his money will be paid back in the case of default. More than 4 minutes have passed.
Jeremy decides to sign up for a trial trading account, answers a question about trading experience and investable assets, hands out his name and email address. While playing around on the trading platform, he carries out a few simulated trades on Austrian stocks.
Inside BankCorp's systems, an algorithm is triggered by the arrival of a new sales lead. The algorithm can access records of past lead profiles and correlate them to the rate of lead to client conversion and to the average revenue generated by client-lead profile pairs.
Based on Jeremy's search keywords, his New York City IP address, the time spent on the bank's website, the pages he visited, the survey responses and the type of simulated trades carried out on the trading platform – from this data – it is inferred that he is likely to become a valuable customer. The algorithm decides that an experienced sales representative with special knowledge about stock trading would do well in contacting him.
Three months later it is determined for sure that Jeremy indeed did become a valuable customer. He conducted a high number of trades and generated a lot of revenue for the bank over this period of time.
A second algorithm is now triggered in BankCorp. The algorithm is interested in the relation between the wsj.com ad, the Google AdWords ad on Austrian stock trading and the value of clients such as Jeremy. The marketing database shows that he and other valuable clients were exposed to a combination of the wsj.com and Austrian stock trading ad. The algorithm set a series of decision in motion. Firstly, it decides to increase the bids on Google keywords containing the terms “trading” and “Austrian stocks”. Secondly, it decides to increase relative spending on the wsj.com marketing channel, while spending less on smartmoney.com. Thirdly, it decides to increase relative spending on the cool-confident investor rich banner ad, while spending on other banner ads are decreased slightly.
BankCorp's CEO is pleased to know, that the days of knowing what half of the marketing budget was wasted, are finally over.
Picture by Tony